A GIS-based comparative study of frequency ratio, statistical index and weights-of-evidence models in landslide susceptibility mapping

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A comparative study of logistic model tree, random forest, and classification and regression tree models for spatial prediction of landslide susceptibility (2017, methodology): “Globally, several statistical models combined with GIS have been used for landslide susceptibility assessment, such as statistical index (Chen et al., 2016a; Constantin et al., 2011; Nasiri Aghdam et al., 2016), index of entropy (IOE) (Constantin et al., 2011; Devkota et al., 2013; Youssef et al., 2”
Evaluating the application of the statistical index method in flood susceptibility mapping and its comparison with frequency ratio and logistic regression methods (2018, methodology): “The following equation is used to calculate Wi weights for each factor (Chen et al. 2016): Wij ¼ In Dij D ¼ In Nij Sij , N S 0 @ 1 A 2 4 3 5 (7) where the weight received for class i of the conditioning factor j is given by Wij; the flood density in class i of the conditioning factor j is given by…”